Dynamic Frequency and Amplitude Estimation for Three-Phase Unbalanced Power Systems Using the Unscented Kalman Filter

Wu, Chenchen; Magaña, Mario E.; Cotilla‐Sanchez, Eduardo

doi:10.1109/tim.2018.2875605

Cited by 34 publications

(17 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several parametric Bayesian methods are useful for the parameter estimation of Gaussian and non-Gaussian systems in which states are Markov process. Different parametric Bayesian estimation methods are available in the literature [9] , [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] , [18] , [19] , [20] , [21] , [22] , [23] , [24] , [25] , [26] , [27] , [28] , [29] , [30] , [31] , [32] are described in Table 1 . For the non-Gaussian systems, Bayesian computation of conditional probabilities has been used for updating the weights involved in the state estimation.…”

Section: Introductionmentioning

confidence: 99%

Stochastic filtering based transmissibility estimation of novel coronavirus

Bansal

Kumar

Singh

et al. 2021

Digital Signal Processing

View full text Add to dashboard Cite

In this study, the transmissibility estimation of novel coronavirus (COVID-19) has been presented using the generalized fractional-order calculus (FOC) based extended Kalman filter (EKF) and wavelet transform (WT) methods. Initially, the state-space representation for the bats-hosts-reservoir-people (BHRP) model is obtained using a set of fractional order differential equations for the susceptible-exposed-infectious-recovered (SEIR) model. Afterward, the EKF and Kronecker product based WT methods have been applied to the discrete vector representation of the BHRP model. The main advantage of using EKF in this system is that it considers both the process and the measurement noise, which gives better accuracy and probable states, which are the Markovian (processes). The importance of proposed models lies in the fact that these models can accommodate conventional EKF and WT methods as their special cases. Further, we have compared the estimated number of contagious people and recovered people with the actual number of infectious people and recovered people in India and China.

show abstract

Section: Introductionmentioning

confidence: 99%

Stochastic filtering based transmissibility estimation of novel coronavirus

Bansal

Kumar

Singh

et al. 2021

Digital Signal Processing

View full text Add to dashboard Cite

show abstract

“…A. Girgis in 1981 [2][3][4]. It mainly applies to the following fields: fundamental and harmonic components detection of grid voltage/current [5][6][7][8][9][10], phase−locked loop synchronization [11][12][13][14][15], power quality detection and compensation equipment [16][17][18][19][20], power disturbance feature extraction and machine classification [21][22][23][24], and etc. In these applications, two conventional models, phase angle vector (PAV) model and orthogonal vector (OV) model, are mainly used.…”

Section: Introductionmentioning

confidence: 99%

Research on Dynamic Modeling of KF Algorithm for Detecting Distorted AC Signal

Nie

2021

Energies

View full text Add to dashboard Cite

Kalman filter (KF) is often based on two models, which are phase angle vector (PAV) model and orthogonal vector (OV) model, in the application of distorted grid AC signal detection. However, these two models lack rigorous and detailed derivation from the principle of dynamic modeling. This paper presents a phase angle vector dynamic (PAVD) model and an orthogonal vector dynamic (OVD) model, which are combined with Kalman filter for detecting distorted grid AC signal. They reveal that the state noise covariance of the dynamic model−based KF is related to the sampling cycle, and overcome the defect of more detecting error for conventional model−based KF. Experiment and evaluation results show that the proposed KF algorithms are reasonable and effective. Therefore, this paper contributes a guiding significance for the application of KF algorithm in harmonic detection.

show abstract

“…Another commonly used estimation technique is the Kalman filter (KF), as a recursive stochastic technique that gives an optimal estimation of state variables of a given dynamic system from noisy measurements [12]- [14]. The main drawback of this algorithm is the bulk calculations that limit its online application due to the requirement of large memory and high-speed microprocessor.…”

Section: Introductionmentioning

confidence: 99%

A High-Speed Master-Slave ADALINE for Accurate Power System Harmonic and Inter-Harmonic Estimation

2020

View full text Add to dashboard Cite

This paper presents a unique twofold adaptive linear neural network (ADALINE) for fast and accurate measurement of fundamental, harmonics, sub-harmonics, inter-harmonics and decaying DC components of a distorted current signal with additive noise. The preceding parallel approach is termed as Master-Slave ADALINE (MS ADALINE). The Slave-ADALINE adopts least mean square (LMS) algorithm with a fixed and large step-size for weight vector adjustment. During the training interval or transients, this filter performs a significant role. On the other hand, the Master-ADALINE uses a variable step-size LMS algorithm for achieving a small steady-state error. At the end of each iteration, the local averages of the squared errors of both the ADALINE's are calculated and weights of the Master-ADALINE are updated accordingly. The amplitudes and phases of desired frequency components can be worked out from Master-ADALINE's weights. The proposed architecture improves the convergence speed by establishing an independent control action between the steady-state error and the speed of convergence. The simulation results of this method under various operating situations are analyzed and compared with single fold ADALINE structure that obeys dynamic step-size LMS (DSSLMS) adaptation rule. Eventually, a scaled laboratory prototype has been developed for the validation of the proposed technique in real-time utilization. This innovative research finding makes the power system smart and precise. INDEX TERMS Adaptive linear neural network (ADALINE), dynamic step-size least mean square (DSSLMS), harmonic estimation, power quality assessment, master-slave (MS).

show abstract

Dynamic Frequency and Amplitude Estimation for Three-Phase Unbalanced Power Systems Using the Unscented Kalman Filter

Cited by 34 publications

References 23 publications

Stochastic filtering based transmissibility estimation of novel coronavirus

Stochastic filtering based transmissibility estimation of novel coronavirus

Research on Dynamic Modeling of KF Algorithm for Detecting Distorted AC Signal

A High-Speed Master-Slave ADALINE for Accurate Power System Harmonic and Inter-Harmonic Estimation

Contact Info

Product

Resources

About